Extreme Multi-label Learning for Semantic Matching in Product Search
Comments Accepted in KDD 2021 Applied Data Science Track
期刊&会议
KDD
ACM SIGKDD Conference on Knowledge Discovery and Data Mining · 会议 · Data Mining
BiblioDAP: The 1st Workshop on Bibliographic Data Analysis and Processing
Comments This workshop will be held in conjunction with KDD' 2021
Q-Learning Lagrange Policies for Multi-Action Restless Bandits
Comments 13 pages, 6 figures, to be published in Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data
FLOP: Federated Learning on Medical Datasets using Partial Networks
Comments To appear in KDD 2021
Maximum Inner-Product Search using Tree Data-structures
Comments Under submission in KDD 2012
Improving Ultrasound Tongue Image Reconstruction from Lip Images Using Self-supervised Learning and Attention Mechanism
Comments Accepted in KDD Workshop (BIOKDD 2021)
Feedback Shaping: A Modeling Approach to Nurture Content Creation
Journal ref KDD 2019: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
Smooth Sequential Optimisation with Delayed Feedback
Comments Workshop on Bayesian causal inference for real world interactive systems, 27th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021)
MTC: Multiresolution Tensor Completion from Partial and Coarse Observations
Comments Accepted in SIGKDD 2021. Code in https://github.com/ycq091044/MTC
Counterfactual Graphs for Explainable Classification of Brain Networks
Comments In proceedings of KDD 2021
Maxmin-Fair Ranking: Individual Fairness under Group-Fairness Constraints
Comments In proceedings of KDD 2021
Device-Cloud Collaborative Learning for Recommendation
Comments KDD 2021
Model-Based Counterfactual Synthesizer for Interpretation
Comments 11 pages in total; To appear in KDD'21;
Topology Distillation for Recommender System
Comments KDD 2021. 9 pages + appendix (2 pages). 8 figures
Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks
Comments One of the winners of 2021 KDD Cup on OGB Large-Scale Challenge
TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Data
Comments 10 pages, 7 figures, to be published in the proceedings of KDD 2021
Zero-shot Node Classification with Decomposed Graph Prototype Network
Comments Accepted by KDD 2021
S-LIME: Stabilized-LIME for Model Explanation
Comments In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '21), August 14--18, 2021, Virtual Event, Singapore
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning
Comments SIGKDD 2021
Efficient Optimization Methods for Extreme Similarity Learning with Nonlinear Embeddings
Comments Published as a conference paper at KDD 2021
Efficient Data-specific Model Search for Collaborative Filtering
Comments KDD 2021
We Know What You Want: An Advertising Strategy Recommender System for Online Advertising
Journal ref Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '21), August 14--18, 2021, Virtual Event, Singapore
AutoLoss: Automated Loss Function Search in Recommendations
Comments Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns
Comments published in KDD 2021; 11 pages;
Dynamic Language Models for Continuously Evolving Content
Journal ref KDD 2021
Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs
Comments The paper is published in KDD 2021
Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes
Comments Accepted at KDD 2021. arXiv admin note: substantial text overlap with arXiv:1909.13857
Fine-Grained System Identification of Nonlinear Neural Circuits
Comments Preprint. 11 pages, 8 figures. Accepted Research Track paper to appear at KDD '21, August 14-18, Virtual Event, Singapore
Theory meets Practice at the Median: a worst case comparison of relative error quantile algorithms
Comments Updated experiments, improved presentation. To appear in KDD 2021
Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data
Comments Accepted to KDD 2021
